A Proposed Architecture - IEEE Xplore

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Sikkim Manipal University. Vikash Varun. Sikkim Manipal University vikashvarunggmail.com. Rohit Kumar. Sikkim Manipal University rohitl 1 [email protected].
System

on Chip for Sensor Network

A Proposed Architecture

Kalpana Sharma Sikkim Manipal University

Vikash Varun Sikkim Manipal University

vikashvarunggmail.com

Abstract - The loss of confidential data results adversary effect while transmission in sensor network. The whole sensor network is then prone to get exposed to the intruder. Hence we need a strong mechanism, rather a hardware oriented solution to protect such sensitive data. In this paper we propose an alternative approach of securing data through an introduction of a hardware component called the Linear Feedback Shift Register (LFSR). The kind of network that we have considered is a hierarchical clustering sensor network. This technique mask all the intermediate, input and output data with some values in order to de-corelate information leaked, if any, so that the original/actual information is not exposed to the intruder. We propose an architecture embedded on a chip of the sensor node which is to be modified to incorporate a new component capable of generating random numbers to mask the output.

Keywords Sensor networks, hierarchical clustering, LFSR, randomization, data security

Security:

Rohit Kumar Sikkim Manipal University rohitl 1 [email protected]

2. LFSR A Linear feedback shift register is made up of two parts: a shift register and a feedback function [2]. The feedback function is simply the XOR of certain bits in the register; the list of these bits is called a Tap Sequence. Figure 1 shows a typical 3 - bit LFSR. The random numbers generated by the LFSR are random enough to be secure to use. It may be noted that the input data to the LFSR can be text, image files or video. In our paper, we propose architecture for the security of sensor nodes with stenographic key (SSNSK) [4] where the LFSR is responsible for key generation. We claim the proposed architecture though simple, is immune to attacks on wireless sensor nodes. Just by providing a Tap Sequence, LFSR can produce the same set of random number in the sender side as well as the receiver side.

1. Introduction Sensor node is similar to a computer node that is capable of doing little processing, sense and communicate with other sensor nodes in the sensor network. The single node of a sensor network is normally termed a Mote. A sensor node consists of the components like a Microcontroller, Transceiver, External Memory, Power source and sensors. It is clear that there is no inbuilt security mechanism embedded in such sensor node. So there is a scope of developing and enhancing the architecture of the sensor node to incorporate security feature at the chip level itself [1]. This paper tries to explore this possibility. As far as the topology of the sensor network for the nodes having this additional feature is concerned, we use a hierarchical clustering in sensor network. In the beginning we started our work by introducing the issues related to sensor network security. The fundamentals of LFSR are given below. Because of the non availability of real sensor node for experimental purpose we could only provide some of the simulated results to support our system later in the paper. We discuss the building block of our system - LFSR in section 2 of the paper. Section 3 deals with the system model proposed. In section 4 we see the related work done in this direction of achieving security of data in sensor network. In section 5 we see the interesting simulation results. This section is followed by the conclusion of the paper.

ISBN 978-89-5519-136-3

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Figure 1: A 3 bit LFSR

3. System Model When the communication takes place between the sender and receiver and vice versa, instead of sending the actual raw data, the data is first randomized using a function 'f generated by hardware component LFSR and sent across the network At the receiver side 'f"' is used to decode the original message. It is clear that if we have a hardware solution for such a system then we definitely need a LFSR as the additional component in the architecture of a sensor node. The tiny sensor nodes have a limited battery life and as a result they should be lightly loaded. For our simulation work we have used a Hierarchical clustering model where we have a base station, a cluster head for all the clusters, a sub cluster head for sub cluster and so on. The cluster head and the sub cluster head are responsible for data aggregation. The reason

Feb. 17-20, 2008 ICACT 2008

behind having so many layers of clustering is because of the proposed node architecture. The tap sequence which is used by the LFSR to generate random numbers acts as the key of the system incorporated in our sensor node architecture. Now if we use the same tap sequence for each communication that takes place in the network and for all the clusters, then in case the tap sequence is exposed to the adversary somehow, the whole network is at risk. To avoid this, for a particular session, all the nodes belonging to clusters and the sub-clusters must be using different set of tap sequence to generate the random numbers. The information about the usage of tap sequence by a sensor node is only visible to the members of the cluster to which it belongs. The other nodes in the neighboring clusters are unaware of the tap sequence usage by their neighbors and vice versa. Figure 2 shows the proposed system model of the sensor node with the LFSR incorporated on the chip level. || Trans - Receiver ||Power

II

111111

11

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Sensor

M Mcrocontroller

LEFSR

1I

ADC

External Memory

Figure 2: Architecture of a Sensor node with an LFSR

The following are the salient features of our proposed model. 1. All the nodes should have LFSR in built within them. 2. Hierarchical clustering with sub clusters is a must for this model. 3. Distribution of the tap sequence is governed by the protocol imposed by the base station to the cluster head and the individual nodes. The rules for the proposed protocol are as follows: a. Tap Sequence Distribution Rule: The following algorithm shows how the tap sequence is assigned to the various nodes in the network. Let us assume that the base station has n tap sequences and k clusters. Here we assume that when the network is initiated the base station chooses a number randomly, say d (where 1